Software Engineer, Applied AI (all levels)
Savvy WealthNYC OfficePosted 1 April 2026
Job Description
Software Engineer, Applied AI (all levels)
ABOUT SAVVY WEALTH:
Wealth management is a $545 billion industry in the US, yet remains archaic and inefficient with low technology penetration. 75% of financial advisors don’t offer digital communication beyond email, and 62% still build financial plans manually in Excel. This leads to a poor client experience and results in financial advisors spending over 70% of their time on non-client facing, manual work.
Savvy is changing that. We’re building the most advisor-centric platform in wealth management: a digital-first solution that modernizes human financial advice. Advisors who partner with Savvy tap into AI-powered software, automated sales and marketing, and seamless back office workflows to scale faster and spend more time with clients.
We’ve raised over $105M to date from Thrive Capital, Index Ventures, Canvas Ventures, Mark Casady (former LPL Financial CEO), and other top-tier investors. Our team is made up of repeat founders and operators who’ve helped build Airbnb, Square, Brex, Carta, Facebook, $200B+ RIAs, and more.
Savvy is at a pivotal point in its growth trajectory, having established strong product-market fit in providing a modern platform to financial advisors. We’ve surpassed $5.1 billion in AUM in less than three years, grown 600%+ in the last 18 months, and are entering the next phase of the company which involves rapid expansion of our product offering and continued revenue growth. Come help us scale!
RESPONSIBILITIES
- Build AI-powered product features for advisors and Savvy operations teams (e.g., copilots, skilled agents, automations, summarization, routing, extraction, recommendations), with a bias toward shipping quickly
- Rapidly prototype and deliver using modern AI tooling (e.g., Claude Code, OpenAI Codex, Cursor, Devin, etc.) while maintaining high engineering standards - from using individual tools to get work done all the way up to leveraging a complex orchestration layer to string together a dozen tools to get things done even faster
- Own the end-to-end product development lifecycle - identify opportunities, design solutions, ship to production, and iterate
- Produce production-grade, readable, maintainable code with good testing discipline
- Partner tightly with Product, Design, Data, and business stakeholders to define scope, de-risk execution, and deliver high-impact outcomes
- Work directly with our customers (financial advisors) to learn their workflows and needs directly from the source
- Run fast!
LEVEL-SPECIFIC EXPECTATIONS
MID-LEVEL
- Implement AI workflows using established patterns (prompting, tool/function calling, retrieval, evals) and improve over time
- Ship well-scoped features independently; break ambiguous problems into concrete tasks
- Contribute to code quality via reviews, tests, and documentation across your team
SENIOR
- Build Savvy AI systems (RAG, classification/extraction pipelines, agentic workflows)
- Establish team patterns for rapid AI development (prompt/versioning strats, eval harnesses (ours and/or with vendors), rollouts, observability, testing)
- Lead projects (medium to large) end-to-end
- Mentor others on best practices as they emerge
STAFF
- Set technical direction for applied AI across multiple product areas
- Drive roadmap shaping with Engineering/Product/Design/Leadership (including CxO leadership)
- Define platform primitives for AI development (shared tooling, libraries, evaluation frameworks, guardrails, cost/perf opts)
- Raise the bar org-wide, even beyond the reach of engineering
MUST HAVE:
- You’re in AI tools day and night, tinkering on work projects as well as personal
- You've built scaling web applications with obvious business impact
- System design expertise as it applies to emerging AI software development trends, for example, system designs that maximize the use of context windows with strong separation between components
- Full-stack proficiency (or evidence you ca ... (truncated, view full listing at source)
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